The Smart Electric Power Grid:An Aerospace Approach

Dr. David M. TralliManager, Civil Programs

National Space Technology Applications Office

Bob Easter, Dr. Martin Feather, and Dr. Gerald VoecksJet Propulsion Laboratory, California Institute of Technology

February 9-10, 2011

NASA Project Management Challenge 2011Long Beach, CA

Used with permission

Overview• Major changes are needed in infrastructure to meet anticipated

energy needs and to address climate issues in the next decade and beyond.

• The smart (advanced) electric power grid is driving development and integration of advanced energy conversion and storage technologies, renewables and clean transportation.

• The smart grid is an engineering system whose complexities span technological, operational, policy, regulatory and market factors. – Planning for its design, development, deployment and sustainability

must be driven by objective, top-down systems analyses.

• The practice of systems engineering and architectural trade off analysis, as used by the aerospace community, is applied to the design and evaluation of architectural options for the smart electric power grid.

The Smart Grid is the seamless integration of an electric grid, a communications network, and the necessary software and hardware to monitor, control and manage the generation, transmission, distribution, storage and consumption of energy

by any customer type.

Moreover, we share a broader vision of the smart grid that encompasses the integration of renewable energy and electric vehicle infrastructure.

Austin Energy

Outline• The Technology Infusion and Maturation Assessment

(TIMA) process developed by the NASA Jet Propulsion Laboratory is used to design and evaluate architectural options for the smart electric power grid and to define corresponding technology roadmaps

• Initial Planning• 2010 California Smart Grid Baseline• Review/capture of 2020 objectives• Key Technology Roadmaps• Use Case Development• TIMA Campaign Phase Project Team Workshops• Analysis, Final Reporting, Recommendations and Integration

Approach• Technology Infusion and Maturation Assessment (TIMA) process and software tool captures

top-level energy policy priorities and functional and business objectives from key technology use cases.

• TIMA was developed by the NASA Jet Propulsion Laboratory over the last decade and applied successfully to technology developments and complex system designs.

• The TIMA process and methodology comprise a suite of innovative software tools for risk balancing and risk management in the context of designing system architecture.

• The TIMA process, combining elicitation, consensus-building, analysis and information visualization, leads to an energy technology roadmap characterized as an optimal set of risk retirement investments addressing R&D and demonstration needs over time, for a given smart grid architecture.

• Presentation Synopsis: The Technology Infusion and Maturation Assessment (TIMA) process developed by the NASA Jet Propulsion Laboratory is used to design and evaluate architectural options for the smart electric power grid and to define corresponding technology roadmaps for distributed energy resources, grid-scale energy storage, command and control for distribution automation, among others.

Systems Engineering• System architecture includes separate but related viewpoints for

describing organizational, functional, physical, informational, and lifecycle aspects of system design.

• An exploration of alternatives in a complex design space helps to highlight key design issues, provides a basis for comparing architectures and selecting an architecture, and promotes finding better design solutions for the project.

• A structured approach to decomposition within each viewpoint (requirements, functional, physical...) provides an effective means of defining complex systems.– Maintaining consistency between corresponding elements in related

viewpoints ensures design integrity.

Smart GridSystem Tradeoff Space

• Defined across RD&D, investment and smart grid functionality parameters captured in legislation (i.e. CA Integrated Energy Policy Reports, Energy Policy Act of 2005, Energy Independence and Security Act 2007) and addressing diverse parameters:– Energy consumption, measurement and efficiency– Energy supply, including distributed energy resources– Energy storage for transportation and stationary sectors– Component and systems technologies, including C3

– Infrastructure (monitoring, storage, transmission, distribution)– Environmental impact– Economic and regulatory considerations

Intellectual Property: Technology Infusion and Maturity Assessment (TIMA) Software Tool Suite

• NPO-21091: Risk Balancing Profiles. Intended as a decision making aid early in the project planning phase.

• NPO-40226: Probabilistic Risk Reduction. Risk is an important and recurring concern in system development. The field of probabilistic risk analysis (PRA) has developed methods to assess risks within complex systems, to deduce the system reliability from knowledge both of the system structure and of the individual system components. – A risk-based planning approach can be combined with traditional

PRA to yields an integrated approach we call “probabilistic risk reduction.” This is well-suited to planning the development of complex systems.

• NPO-20741: Defect Detection and Prevention (DDP). User-friendly environment to generate a tree of failure modes and a tree of requirements and evaluate the impact of each failure mode on each requirement. This weighs the failure modes by the relative importance. – The product of the failure mode importance and the effectiveness of the

planned PACT provides the residual risk for each failure mode. • NPO-43474: End-to-End Project Engineering. If risk assessment is

done only at the culmination of the design process, the space of remaining options among which to decide is severely constrained. If done early and continued throughout the design process, it can be used to look ahead at the development plan and operational/functional scenarios before large and irrecoverable investments are made.

Intellectual Property: Technology Infusion and Maturity Assessment (TIMA) Software Tool Suite

• NPO-40456: Using Dissimilarity Metrics to Identify Interesting Designs. Finding a preferred solution to a complex design problem is challenging. On the one hand the problem space is too large and convoluted for human comprehension, while on the other hand it is infeasible to elicit the entirety of design knowledge required for fully automatic problem solving. – We face this challenge repeatedly when planning the development of technologies

for spacecraft applications!• Search, data mining, and visualization capabilities are features of the risk

management tool suite to support this risk-centric design methodology developed and applied at NASA/JPL. – Numerous risk abatement options give rise to a huge space of potential design

solutions. – Demonstrated on the selection of risk abatement solutions for design of advanced

technology, and to plan technology development for future spacecraft missions.

Intellectual Property: Technology Infusion and Maturity Assessment (TIMA) Software Tool

Smart Grid Technology RoadmapUse Cases

1) Evaluation of the potential impact of GHG reduction goals, as defined in Assembly Bill 32 (Nunez, Chapter 488, Statutes of 2006), on meeting the energy growth needs of California through new and innovative smart grid technologies.

Objective: Reduce GHG emissions to 1990 levels across all sources in 2020

2) Natural gas impacts and benefits of the smart grid, including consideration of CHP.Objective: Additional 5,400MW of combined heat and power in 2020.

3) Command and communications technologies (C2), Distribution Automation, including consideration of AMI.

Objectives: Electricity peak demand reduction goal of 4,885MW in 2013; DR: Demand response that reduces TBD % of peak demand in 2020.

4) C2 and PHEVsObjective: Accommodation of PHEVs into smart grid.

5) Bio-sources and Fuel Cell energy storage.Objective: 20% of renewable power supplied by biopower sources in 2020 (~20,000 GWh/year).

6) Large scale battery storage, integration of solar and wind, intermittency. Objective: 33% of generation by renewables (~104,000 GWh/yr) in 2020.

Integrated Energy Policy ReportEPRI Report 2008

Integrating New and Emerging Technologies

Use Case #1

Use Case #2

Use Case #3

Use Case #4

Use Case #5GHG Reductions

Use Case #6Natural Gas Ratepayer Impacts

TIMA

Top-Level Requirements/Objectives

Objectives

Risks/Barriers

Investments/Demos/Actions

System Architecture Options

Trade Space Analysis

Residual Risk Profiles

Investment Options & Actions

RD&D Roadmap

Risk Retirement

Analytical process flow for integration of top-level requirements with a nominal (illustrative here) minimal number of use case objectives for developing a California Smart

Grid 2020 system architecture and recommended RD&D roadmap. GHG reductions and natural gas ratepayer cases also developed as part of this Project.

California Energy Policy Targets

Criteria to assess contribution of smart grid technologies in support of the target goals

Climate change – improve the environmental impact of the grid on California (reducing GHG emissions)

How to meet AB32 mandates for reductions of GHG emissions to 1990 levels by 2020, while incentivizing the market for rapid adoption of new and innovative smart grid technologies.

Energy efficiency – increase efficiency of the grid

How to meet cost-effective energy efficiency in electricity and natural gas supply while reducing demand, and supporting legislated initiatives in a technologically sound and viable manner.

Demand response – improve overall grid system operational reliability, availability, sustainability and maintainability

How to mature a power delivery system fully equipped with control and communications that allow integration of distribution automation functions, and allows for the smooth operation of renewable energy sources.

Renewable energy – ability to increase penetration of renewable technologies on the California smart grid

How can the smart grid architecture be designed to enable the integration of renewable energy supplies that meet RPS targets while mitigating the risk of intermittency through large-scale energy storage, distributed storage and smaller-scale DER.

Distribution systems – reduce costs of operations [and maintenance] of the grid

How will C2 structures be implemented at the distribution nodes in a manner that is operationally sustainable, meets consumer-level requirements for quality of service, new end-use applications, and offers good cost-benefit in O&M, security, etc.

Key Technologies Identified Through Series of Study Workshops

• Fast Storage• Rooftop Photovoltaics • Demand Aggregation• Biomass, Biogas and Fuel Cells• Microgrid accommodation• Combined Heat and Power (CHP)• Command, Control & Communications (C3)• Distribution Automation• Advanced Metering Infrastructure (AMI)• PHEV/PEV accommodation• Intermittent solar & wind integration (RPS)

14

Key California Energy Policy Goals

1) 33% of generation by renewables (~104,000 GWh/yr) in 20202) 20 % of renewable power supplied by biopower sources in 2020

(~20 GWh/year)3) 3,000 MW of new rooftop Solar PV by 2016 (~5000 GWh/yr) 4) 10% reduction in total forecasted electrical energy consumption in

20165) 5,400MW of combined heat and power in 2020 6) Demand response that reduces TBD % of peak demand in 2020 7) Electricity peak demand reduction goal of 4,885MW in 2013 8) All new residential construction is net zero energy in 2020 9) Reduce GHG emissions to 1990 levels across all sources in 2020

15

GHG

Net zeroconstruction

33% RPS

Rooftop PV

CHP

Biomass

Energy demand/consumption

Energy supply/generation

Peak reduxDemandResponse

Total forecastedconsumption

reduction2

76

41

8

3

9

5

NG

Interrelationships between the 9 High-Level Goals

Renewable Sources[Goal - 33% of Total Electricity]

Wind

LocalDistributed

Remote Central

Storage (ESG)Batteries, CAES,

capacitors, flywheels

Solar

LocalDistributed

Remote Central

Storage (ESG)Batteries, capacitors, thermal, flywheels

Thermal - PV

Wave/Hydro Geothermal

CHP[Additional 5.4 GW by 2020]

Natural Gas

CHP

Microturbine(~10’s kW)

CommercialGas Turbine

(~50-100’s kW)

Reciprocating Engines

(~50-100’s kW)

Fuel Cells(~1-5 MW)

SteamTurbine (MWs)

Electricity CHP Electricity

Co-genElectricityCHP Electricity CHP Electricity

Biomass

Solid Muni-cipal Waste

AgriculturalWaste

ForestByproducts

OtherSources

WastewaterTreatment

Gasification, pyrolysis, anerobic digestion – gas cleanup/concentration

[~ 20 GWh/yr by 2020]

Residential Microgrid Commercial Microgrid

TransmissionPassive

Industrial Microgrid

ActivePassive ActiveActivePassive [5-50 MW] [2-20 MW] [1-5 MW]

UTILITY GRID

Batteries, H2, EV Batteries, H2, Thermal, EV Batteries, H2, Thermal, EV, UltracapsStorage Storage Storage

Rooftop PV

Passive = utility integrated and utility owned, controlled and operatedActive = utility integrated, but consumer &/or third party owned/controlled/operated

[No micro-grid con-nection]

18GEV

Total Electricity System Power in California

2009 Total California In-State Power Generation

Fuel Type

In-State Generation

(GWh)

California In-State Power

(%)

Northwest

Imports

Southwest

Imports

Total System Power

Coal 3,735 1.8% N/A N/A N/A

Large Hydro

25,094 12.2% N/A N/A N/A

Natural Gas

116,716 56.7% N/A N/A N/A

Nuclear 31,509 15.3% N/A N/A N/A

Oil 67 0.0% N/A N/A N/A

Other 7 0.0% N/A N/A N/A

Renew-ables

28,567 13.9% N/A N/A N/A

Biomass 5,685 2.8% N/A N/A N/A

Geothermal

12,907 6.3% N/A N/A N/A

Small Hydro

4,181 2.0% N/A N/A N/A

Solar 846 0.4% N/A N/A N/A

Wind 4,949 2.4% N/A N/A N/A

Total 205,695 100.0% 19,929 71,201 296,827

Source: EIA, QFER, and SB 105 Reporting Requirements Note: Due to legislative changes required by Assembly Bill 162 (2009), the California Air Resources Board is currently undertaking the task of identifying the fuel sources associated with all imported power entering into California. 1.In-state generation: Reported generation from units 1 MW and larger.

2008 Total System Power in Gigawatt Hours

Fuel TypeIn-State

Generation[1]

Northwest

Imports[2]

Southwest

Imports[2]

Total System Power

Percent of Total System Power

Coal* 3,977 8,581 43,271 55,829 18.21%

Large Hydro

21,040 9,334 3,359 33,733 11.00%

Natural Gas

122,216 2,939 15,060 140,215 45.74%

Nuclear 32,482 747 11,039 44,268 14.44%

Renew-ables

28,804 2,344 1,384 32,532 10.61%

Biomass 5,720 654 3 6,377 2.08%

Geothermal

12,907 0 755 13,662 4.46%

Small Hydro

3,729 674 13 4,416 1.44%

Solar 724 0 22 746 0.24%

Wind 5,724 1,016 591 7,331 2.39%

Total 208,519 23,945 74,113 306,577 100.0%

Source: 2008 Net System Power Report - Staff Report, Publication number CEC-200-2009-010, to be considered for adoption July 15, 2009. (PDF file, 26 pages, 650 kb) EIA, QFER, and SB 105 Reporting Requirements *Note: In earlier years the in-state coal number included coal-fired power plants owned by California utilities located out-of-state. 1.In-state generation: Reported generation from units 1 MW and larger. 2.Net electricity imports are based on metered power flows between California 3.and out-of-state balancing authorities. The resource mix is based on utility power source disclosure claims, contract information, and calculated estimates on the remaining balance of net imports.

19GEV

Wind Energy Contribution to 2020 CA Grid

• Remote - Central Source– Large windmills/farms in desert, for example

• Local – Distributed Source– Smaller windmills/farms in Valleys and in close proximity to towns

• 2009 Total is 4.949 TWh (2.43% of Total in-state Electrical Energy)

Wind Energy Production Status

Wind Energy Status• Remote – Central Source

– Transmission lines will be required to transfer electricity to customers– New transmission lines will need to be built and current transmission lines will

need to be expanded or updated– Some form of storage (batteries, hydrogen, fuel cells, turbines, etc.) will be

required to accommodate this expansion– Where is the best storage location – at the generator or near the customer

(DR, CC, and microgrids)• Local – Distributed Source

– Smaller windmills in Valleys and in close proximity to towns– Suitable for microgrid architecture and DR, CC operations

20GEV

Solar Energy Contribution to 2020 CA Grid

• Remote - Central Source– Large solar panels (PVs) in Desert– Large solar-thermal generators in Desert

• Local – Distributed Source– Rooftop PVs in residential, commercial and industrial settings

• 2009 Total is 846 GWh (2.43% of Total In-state Electrical Energy)– 5000 GWh rooftop by 2016 (an increase of 5.9 times 2009 total level, 4.8% of 2020 total)

Solar Energy Production Status

Solar Energy Status• Remote – Central Source

– New transmission lines will need to be built and current transmission lines will need to be expanded or updated

– Some form of storage (batteries, hydrogen, fuel cells, turbines, etc.) will be required to accommodate this expansion for continuity of power

– Where is the best storage location – at generation or at load (DR, CC, and microgrids)?

• Local – Distributed Source– Smaller PV sites in residential, commercial and industrial that are close

proximity to consumer– Suitable for microgrid architecture and DR, CC operations

21GEV

• Direct conversion to electricity– Electrochemical conversion from hydrogen to DC electricity– No mechanical generator required– Conversion efficiency is high (direct conversion ~50% or higher)

• Waste heat can be used in various scenarios– Different fuel cell types have different amounts and grades of heat– Demonstrations of waste heat recovery and use have illustrated this feature

for the past thirty years• Various operating conditions possible

– Some fuel cells can be efficiently operated over a range of output– Many fuel cells can be modularized and combined to provide a range of

outputs as a function of the demand – Some fuel cells can simultaneously generate electricity, heat and hydrogen for

added flexibility in consumer demands

Natural Gas as Source of Electricity and CHPAdvantages of Fuel Cells

22GEV

• Molten Carbonate Fuel Cells– Operate at 600 C (Provide high-grade waste heat)– Can provide internal fuel processing to operate fuel cell– Operate at ~60% efficiency (heating value of fuel to electricity)– Operate on range of gaseous fuels (methane, low Btu gases, propane, liquid fuels)

• Phosphoric Acid Fuel Cells– Operate at 200 C (Provide both high and low grade waste heat)– Can be integrated with SMR as external fuel processor– Operate at ~ 50% thermal efficiency– Operate on range of gaseous fuels

• Proton Exchange Membrane (PEM) Fuel Cells– Operate at 80 C (Provide low-grade waste heat)– Operates from hydrogen– Operates at ~ 60% thermal efficiency

• Solid Oxide Fuel Cells– Operate at 800 C– Can provide internal fuel processing to operate fuel cell– Operate at ~60% efficiency

Fuel Cell System Options (Electrochemical Conversion of Fuel Directly into DC) for

Biomass CHP/Electricity

• From DOE-CEC Microgrid Workshop / Navigant Consulting:– A microgrid is an integrated power delivery system consisting of interconnected loads and distributed energy

resources (DER) which as an integrated system can operate in parallel with the grid or in an intentional island mode.

– The integrated DER are capable of providing sufficient and continuous energy to a significant portion of the internal load demand even in island mode.

– The microgrid possesses independent controls and can island with minimal service disruption.

• From DOE-CEC Microgrid Workshop / Navigant Consulting: “What unique value(s) does a microgrid provide beyond DG alone, and who would pay for it?”

– The microgrid allows operation with a larger power system; this provides two key capabilities:• Flexibility in how the power delivery system is configured and operated• Optimization of a large network of load, local Distributed Energy Resources and the broader power

system– These two capabilities can deliver three important value propositions:

1. Custom Energy Solutions: Provide customized power to individual customers/tenants or groups of customers/tenants

2. Independence/Security: Support enhanced energy and infrastructure availability and security3. Reduced energy cost: Provide end users with less expensive energy over current rates.

Microgrids

Microgrid Design, Construction, Interconnection and Operation

Residential Microgrid

Commercial Microgrid

TransmissionPassive

NG CHP, storage,PV, PHEV, EV

Industrial Microgrid

ActivePassive Active

All microgrids connected to grid operations

Passive = utililty integrated and utility owned, controlled and operatedActive = utility integrated, but consumer &/or third party owned/controlled/operated

NG/biomass CHP, storage,H2, PV, Wind, PHEV, EV

[5-50 MW] [2-20 MW] [1-5 MW]

NG/biomass CHP, storage,H2, PV, Wind, PHEV, EV

ActivePassive

Interconnection, within each microgrid and across the grid, is integrated to permit uniform communication, control, load distribution, demand response, etc. according to customers’ needs and overall electricity availability. Islanding among microgrids is possible.

24

Stand alone microgrids

GEVoecks25

[Goal - 10% Total Electricity by 2016]

[Goal – Demand response reduces peak demand ]

[Goal – Reduce peak demand of ~4.9 GW by 2013]

Passive = utility integrated and utility owned, controlled and operatedActive = utility integrated, but consumer &/or third party owned/controlled/operated

UTILITY GRID

Residential Microgrid

Interface between local electrical source and storage/distribution (Batteries, H2, EV) within a microgrid community

Local Electrical Source- Renewables- PV- Natural gas

Interface between grid connect and storage/Distribution within a microgrid community

Storage [1-5 MW]Size and type of storage device is a function of several parameters:- Community needs- Size of electrical source- Cost of storage- Integration with grid- Controls complexity- Local electricity source- Location

ControlsAt the local source of electricity interconnect:- HAN, AMI- Storage quantity level- C2

- MEM- Microgrid controlAt the grid interconnect:- Storage quantity level- DA, Microgrid control- Central Manager

Baseload electricity supply via grid

Peaking supply from local storage

Electrical SourceTo Residences- Local generation- Baseload supply

Remote Storage (ESG)Batteries, Capacitors, Thermal,

Flywheels, Ultracapacitors,CAES, Hydro

Batteries- Flow type- Li ion- NaS

H2 production - Fuel Cell - Electrolysis

Efficiencies =

Goal Focus- Improved Appliances- Demand Response- Grid Peak Reduction- Grid Distribution Loss Reduction- Generator Efficiency- Conversion Efficiency- Fault Isolation- Safety - Efficient Use (EV)- GHG Reduction

CHP

Roadmap Sectors: Reduction in Electricity Consumption

Reduction in Electricity Generation and GHG Emissions

Use Reduction Distribution Efficiency

ImprovedAppliances &

other Conversion

DemandResponse

ControlsTechnology

Microgrids

Network controls, storage, PHEV, EV

Production Efficiency

MicrogridsRemote Central

Utility grid,commercial,industrial,residential

Source, storage,network, Integration

Storage, source,grid connection,

transmission, CHP

Commun-ications

Technology

4

6

7

[Goal - 10% Total Electricity by 2016][Goal – Demand response reduces peak demand ]

[Goal – Reduce peak demand of ~4.9 GW by 2013]

GHG to 1990 levels across all sources in 2020

9

26

Principal Elements of TIMA• Objectives – the characteristics of the desired end-state• Barriers – the impediments, risks, obstacles… that get in the way of

attaining the Objectives• Actions – the possible actions that could be taken to overcome Barriers,

and thereby attain the Objectives

• Objectives and Barriers are linked, to indicate which Barriers get in the way of which Objectives, and to what extent they get in the way (referred to in the software as “impact”)

• Actions and Barriers are linked, to indicate which Actions overcome which Barriers, and to what extent they overcome them (referred to in the software as “effect”).

– In some cases, an action will make some Barriers worse (either introducing new Barriers that were not relevant before, or making existing Barriers even worse).

Technology Infusion and Maturity Assessment (TIMA) Tool/Process

IEPR “Objectives” against which Smart Grid plans will

be assessed

“Actions” from which to pick and choose the makeup of alternate

Smart Grid plans

“Barriers” – all the concerns, risks etc. that could impede attainment of

objectivesAdditional information is

kept on each item

The industry partners will help complete these parameters, and provide the crucial interrelationships. From this information alternate Smart Grid plans and a technology roadmap can be evaluated.

Smart Grid System Architecture

Objectives x Barriers

Objective’s row highlighted in blue

Barrier’s column highlighted in red

Rows are ObjectivesColumns are BarriersThe cell numbers indicate “impact” - how much each Barrier obstructs each Objective.These impact numbers are proportions, i.e.,1 = total obstruction0.7 = major obstruction0.3 = modest obstruction0.1 = minor obstructionBlank = no obstruction

The solid red circle is there to draw viewers’ attention to this Barrier

The solid blue circle is there to draw viewers’ attention to this Objective

Objectives

Mitigations

Risks

Mitigations incur costs; usually can’t afford them all, so must select judiciously.The highly cross-coupled nature of this information is the reason why successful technology acquisition is so hard to achieve!

E.g., 50 objectives, 31 risks, 58 mitigations from actual JPL technology study: “topology” of this data is shown below (in addition, every link has a quantity associated with it: how much each risk detracts from each objective; how much each mitigation reduces each risk (in some cases, increases – the red lines)

Simple model, convoluted data

Actions x BarriersRows are Actions, Columns are Barriers, cell numbers indicate “effect” - how much each Action overcomes each Barrier. The numbers are proportions, e.g., 1 = totally overcomes; 0.7 = mostly overcomes; 0.3 = moderately overcomes; 0.1 = slightly overcomes; Blank = no help; Negative means makes the Barrier worse, either it introduces it (e.g., 0.3 = introduces some) or magnifies it (e.g., -1.3 = magnifies by 1.3)

Cost

Bene

fit

(exp

ecte

d att

ainm

ent o

f obj

ectiv

es)Region of diminishing returns

Sweet spot!Significant improvement possible; excellent case for more investment!

Sub-optimal interior

High Cost, Low Benefit

Low Cost, High Benefit

Low Cost, Low Benefit

High Cost, High Benefit

x Each point represents a selection of mitigations, located by its cost (horizontal position) and benefit (vertical position).

300,000 points plotted here

58 mitigations = 258 (approx 1017) ways of selecting from among them.Heuristic search for near-optimal solutions extended across the entire cost range to reveal shape of the cost-benefit trade space.

Cost-Benefit Tradeoff Space

Actions and Objectives AttainmentEach row corresponds to one of the Objectives – color indicates proportion of that objective’s attainment

Comparison of Mitigation OptionsE.g., one column per risk

Three selections of mitigations are compared – a baseline selection, an alternate, and the empty set

Black = increase of alternate over baseline

Yellow = decrease of alternate over baseline

Green = unmitigated

Documentation Generation

Summary – Preliminary Findings• Distributed generation needs distributed storage to achieve the greatest efficiency

and operational benefits.• Storage is needed for a variety of smart grid applications—such as peak shaving,

islanding, VAR support, renewable energy integration, PEVs, frequency regulation• Biomass offers significant potential for reducing the GHG and adding to the

distributed generation.• Microgrids can be assembled in many different architectures and adapted to

accommodate several different electrical and thermal requirements, all resulting in significant energy and GHG savings.

• Microgrids and distributed generation/storage systems can take advantage of the NG distribution system, as well as renewable energy generation, to achieve greater savings through hybridization of operations.

• Demonstrations of microgrids and distributed generation/storage need to be pursued in different settings to illustrate the value to utilities and customers.

• Fuel cells offer significant energy savings and reduced GHG through use of NG and CHP.

Summary – Approach• The smart grid is an engineering system whose complexities span technological, operational,

policy, regulatory and market factors. – Planning for its design, development, deployment and sustainability must be driven by

objective, top-down systems analyses. – Driving development and integration of advanced energy conversion and storage technologies,

renewables and clean transportation.

• The practice of systems engineering and architectural trade off analysis, as used by the aerospace community, is applied herein to the design and evaluation of architectural options for the smart electric power grid.

• Technology Infusion and Maturation Assessment (TIMA) allows the linkage of top-level energy policy priorities with physical, functional and business objectives from key technology use cases, by looking at barriers to objectives attainment and actions to mitigate those barriers.

• The TIMA process, combining elicitation, consensus-building, analysis and information visualization, leads to energy technology roadmap recommendations characterized as an optimal set of risk retirement investments addressing R&D and demonstration needs over time (2010 baseline to 2020), for a given smart grid architecture.

Summary – Preliminary Findings• Distributed generation needs distributed storage to achieve the greatest efficiency

and operational benefits.• Storage is needed for a variety of smart grid applications—such as peak shaving,

islanding, VAR support, renewable energy integration, PEVs, frequency regulation• Biomass offers significant potential for reducing the GHG and adding to the

distributed generation.• Microgrids can be assembled in many different architectures and adapted to

accommodate several different electrical and thermal requirements, all resulting in significant energy and GHG savings.

• Microgrids and distributed generation/storage systems can take advantage of the NG distribution system, as well as renewable energy generation, to achieve greater savings through hybridization of operations.

• Demonstrations of microgrids and distributed generation/storage need to be pursued in different settings to illustrate the value to utilities and customers.

• Fuel cells offer significant energy savings and reduced GHG through use of NG and CHP.